Exists a function in LightningChartJs to get all visible points from a line or point series in a chart?
If I zoom the chart I want to show something if no visible points available. In some cases I have breaks in my data.
For now I have to check the range and filter all points within this range, but that seems not to be very performant. I guess LC is aware of all the visible points and can give me that.
I would very much welcome any thoughts on the subject or other solutions. Thanks.
LightningChart JS doesn't track the data points that are visible at any time. So the method that you have used to solve the issue is the best way currently.
Something like this seems to be reasonably performant.
function getDataInRange(data, rangeStart, rangeEnd){
const inRangeData = []
const dataLength = data.length
let curPoint
for(let i = 0; i < dataLength; i += 1){
curPoint = data[i]
if(curPoint.x >= rangeStart && curPoint.x <= rangeEnd){
inRangeData.push(curPoint)
}
}
return inRangeData
}
On my personal machine it can process 1 million points in ~10ms ± 2ms. If you only want to know that a point is visible in the range then you could just break the loop as soon as a single point is in the visible range.
Late to the game but for anybody googling:
If you already have a chart defined and it happens to be named 'chart' (otherwise change chart to your chart's object name), you can track the visible start and end data points like this:
axisX = chart.getDefaultAxisX()
window.axisXScaleChangeToken = axisX.onScaleChange((s, e) => {
window.axisXVisibleDataRangeStart = s
window.axisXVisibleDataRangeEnd = e
})
let visiblePoints = [];
for(let i of cur.data){
if(i[0] > window.axisXVisibleDataRangeStart && i[0] < window.axisXVisibleDataRangeEnd) visiblePoints.push(i)
}
Every time the X axis is scaled/zoomed/moved, axisXVisibleDataRangeStart and axisXVisibleDataRangeEnd will change. You're then iterating over where your data points are stored (cur.data in my case and the example) and comparing: If timestamp is within range, push to visiblePoints.
(I am using OHLC where data[0] is the timestamp. Your comparison might be to an object array where {x:} is the value youre looking to compare. You get the idea.)
To remove the listener and stop the logging:
axisX.offScaleChange(window.axisXScaleChangeToken)
Related
I have an ordered data set of decimal numbers. This data is always similar - but not always the same. The expected data is a few, 0 - 5 large numbers, followed by several (10 - 90) average numbers then follow by smaller numbers. There are cases where a large number may be mixed into the average numbers' See the following arrays.
let expectedData = [35.267,9.267,9.332,9.186,9.220,9.141,9.107,9.114,9.098,9.181,9.220,4.012,0.132];
let expectedData = [35.267,32.267,9.267,9.332,9.186,9.220,9.141,9.107,30.267,9.114,9.098,9.181,9.220,4.012,0.132];
I am trying to analyze the data by getting the average without high numbers on front and low numbers on back. The middle high/low are fine to keep in the average. I have a partial solution below. Right now I am sort of brute forcing it but the solution isn't perfect. On smaller datasets the first average calculation is influenced by the large number.
My question is: Is there a way to handle this type of problem, which is identifying patterns in an array of numbers?
My algorithm is:
Get an average of the array
Calculate an above/below average value
Remove front (n) elements that are above average
remove end elements that are below average
Recalculate average
In JavaScript I have: (this is partial leaving out below average)
let total= expectedData.reduce((rt,cur)=> {return rt+cur;}, 0);
let avg = total/expectedData.length;
let aboveAvg = avg*0.1+avg;
let remove = -1;
for(let k=0;k<expectedData.length;k++) {
if(expectedData[k] > aboveAvg) {
remove=k;
} else {
if(k==0) {
remove = -1;//no need to remove
}
//break because we don't want large values from middle removed.
break;
}
}
if(remove >= 0 ) {
//remove front above average
expectedData.splice(0,remove+1);
}
//remove belows
//recalculate average
I believe you are looking for some outlier detection Algorithm. There are already a bunch of questions related to this on Stack overflow.
However, each outlier detection algorithm has its own merits.
Here are a few of them
https://mathworld.wolfram.com/Outlier.html
High outliers are anything beyond the 3rd quartile + 1.5 * the inter-quartile range (IQR)
Low outliers are anything beneath the 1st quartile - 1.5 * IQR
Grubbs's test
You can check how it works for your expectations here
Apart from these 2, the is a comparison calculator here . You can visit this to use other Algorithms per your need.
I would have tried to get a sliding window coupled with an hysteresis / band filter in order to detect the high value peaks, first.
Then, when your sliding windows advance, you can add the previous first value (which is now the last of analyzed values) to the global sum, and add 1 to the number of total values.
When you encounter a peak (=something that causes the hysteresis to move or overflow the band filter), you either remove the values (may be costly), or better, you set the value to NaN so you can safely ignore it.
You should keep computing a sliding average within your sliding window in order to be able to auto-correct the hysteresis/band filter, so it will reject only the start values of a peak (the end values are the start values of the next one), but once values are stabilized to a new level, values will be kept again.
The size of the sliding window will set how much consecutive "stable" values are needed to be kept, or in other words how much UNstable values are rejected when you reach a new level.
For that, you can check the mode of the values (rounded) and then take all the numbers in a certain range around the mode. That range can be taken from the data itself, for example by taking the 10% of the max - min value. That helps you to filter your data. You can select the percent that fits your needs. Something like this:
let expectedData = [35.267,9.267,9.332,9.186,9.220,9.141,9.107,9.114,9.098,9.181,9.220,4.012,0.132];
expectedData.sort((a, b) => a - b);
/// Get the range of the data
const RANGE = expectedData[ expectedData.length - 1 ] - expectedData[0];
const WINDOW = 0.1; /// Window of selection 10% from left and right
/// Frequency of each number
let dist = expectedData.reduce((acc, e) => (acc[ Math.floor(e) ] = (acc[ Math.floor(e) ] || 0) + 1, acc), {});
let mode = +Object.entries(dist).sort((a, b) => b[1] - a[1])[0][0];
let newData = expectedData.filter(e => mode - RANGE * WINDOW <= e && e <= mode + RANGE * WINDOW);
console.log(newData);
I am wondering how should I implement KCL using JavaScript. I have several current meter that to detect the value of current along a line.
I came out with a simple program but was unable to think about how to implement KCL efficiently.
var currentPointsDBA = new Array(); // Data from electricity meter will be captured and store in this array
var totalCurrentMDB = new Array(); // Total current from adding will be stored in array. Each index represents 1 distribution board.
const totalBusBar = 5;
for (z=0; z<currentPointsDBA.length(); z++){
totalCurrent += currentPoints[z];
}
totalCurrentMDB[0] = totalCurrent;
var currentCheck = [
{
name: DBA, number: 0, threshold: 0
}];
for(i=0; i<totalBusBar; i++){
var totalCurrentCheck = currentCheck[i];
if(totalCurrentMDB[totalCurrentCheck.number] != 0){
//DO SOMETHING
}
}
I realized with this, the condition will never be met as I am adding the current without using the concept of current entering the node is equals to current exiting a node.
Another difficulty that I was facing was to have an algorithm that can be used to calculate positively and negatively for KCL.
Inputs would be a power line that will be connected to a transducer(meter to measure current). Output is also current that is connected to a meter.
For the Point 1,2,3,4,5 it will be replaced with the meters. Basically, I would want an algorithm to have Sum of DBA = Point 1+2+3+4+5. However, point 1 is bi-directional. It can act as input or output. The issue will be to figure out how the current direction is and use that to determine as input or output.
I want to check if a Hand in a Leap Motion Frame is currently a Fist.
The usually suggested method is to look for hand.grabStrength with a value of 1. The problem is that the value jumps to 1 even with a "Claw-Like" Hand, or anything else with very slightly curled fingers.
Another approach would be to check on each finger if it is extended. But this has a similiar issue, Fingers only count as extended if they are completely straight. So even if i check for all fingers to be not extended, the same issue as above occurs (claw-like hands get recognized as grabbed).
Combining these two methods also does not solve the issue, which is not surprising given that they both suffer from the same problems.
Now, we do have all the bones of each finger available, with positions and everything. But I have no idea where to start with the math to detect if a finger is curled.
Basically I have this setup for now:
var controller = Leap.loop(function(frame){
if(frame.hands.length>0){
//we only look at the first available hand
var hand = frame.hands[0];
//we get the index finger only, but later on we should look at all 5 fingers.
var index = hands.fingers[1];
//after that we get the positions of the joints between the bones in a hand
//the position of the metacarpal bone (i.e. the base of your hand)
var carp = index.carpPosition;
//the position of the joint on the knuckle of your hand
var mcp = index.mcpPosition;
//the position of the following joint, between the proximal and the intermediate bones
var pip = index.pipPosition;
//the position of the distal bone (the very tip of your finger)
var dip = index.dipPosition;
//and now we need the angle between each of those positions, which is where i'm stuck
}
});
So, how do I get the angle between two of those positions (carp to mcp, mcp to pip, pip to dip)? Any ideas?
Alright, I think I found a sort of working approach to detect an actual fist, and not a claw.
First off, instead of the positions of the joints, we need the distance Vectors for each Bone.
Then we calculate the Dot product between the Metacarpal and the Proximal bone, as well as the dot Product between the Proximal and the Intermediate Bone. We can ignore the Distal bone, it doesn't change the result too much.
We sum all the calculated dot products (10 in total) and calculate the average out (we divide by 10). This will give us a value between 0 and 1. A Fist is beneath 0.5 and everything above that is basically not a fist.
Additionally you might also want to check for the amount of extended fingers on a Hand and check if it is 0. This will ensure that a "Thumbs-up" and similiar 1-digit poses do not get recognized as a Fist.
Here is my implementation:
const minValue = 0.5;
var controller = Leap.loop(function(frame){
if(frame.hands.length>0)
{
var hand = frame.hands[0];
var isFist = checkFist(hand);
}
});
function getExtendedFingers(hand){
var f = 0;
for(var i=0;i<hand.fingers.length;i++){
if(hand.fingers[i].extended){
f++;
}
}
return f;
}
function checkFist(hand){
var sum = 0;
for(var i=0;i<hand.fingers.length;i++){
var finger = hand.fingers[i];
var meta = finger.bones[0].direction();
var proxi = finger.bones[1].direction();
var inter = finger.bones[2].direction();
var dMetaProxi = Leap.vec3.dot(meta,proxi);
var dProxiInter = Leap.vec3.dot(proxi,inter);
sum += dMetaProxi;
sum += dProxiInter
}
sum = sum/10;
if(sum<=minValue && getExtendedFingers(hand)==0){
return true;
}else{
return false;
}
}
While this works like it should, I doubt that this is the correct and best approach to detect a Fist. So please, if you know of a better way, post it.
Solution works perfect, any chance you could explain why you divide by 10 and why the minValue is 0.5? Thanks!
Well, it doesn't work that good, to be honest. I'll soon start to work on a little project that has the goal to improve the detection of fists with Leap Motion.
Regarding your questions, We divide the sum by 10 because we have 2 Bone Joints per finger, with 5 fingers. We want the average value from the sum of all those calculations, because not all fingers will be angled in the same way. So we want some value that encompasses all of these values into a single one: the average value. Given that we have 10 calculations in total (2 per each finger, 5 fingers), we divide the sum of those calculations and there we go. We will get a value between 0 and 1.
Regarding the minValue: Trial&Error. In a project of mine, I used a value of 0.6 instead.
This is another problem of this approach: ideally a flat hand should be a value of nearly 0, while a fist should be 1.
I know it is an old topic but if you guys still around the answer could be simpler just by using sphereRadius() ;
I found "grabStrength" is good
I am working on a D3 bar chart that would visualize a few ranges (massaged data already coming from somewhere else) and allow the user to select a number of ranges for filtering of their search criteria.
Fiddle here:
http://jsfiddle.net/qear2g9b/
The mechanics of it work pretty well I think. The part I am running into problems with, is capturing user input and mapping it to the data.
Once finished, the user should be able to select and drag a range (along the x axis) for the categories they would like to see. I am using d3.brush to let the user select an area on the chart (I haven't looked into how to get it to select the entire chart height yet). On endbrush I am capturing coordinates that I need to map back to the categories that were on the x axis.
Since it is an ordinal scale, it doesn't have invert, so I am kind of suck. Any help would be much appreciated.
Code snippet below:
function brushend() {
console.log("BRUSH END");
console.log(brush.extent());
var pos = brush.extent();
var out = [];
for (var i = 0; i<pos.length;i++) {
for (var j = 0; j<pos[i].length;j++) {
console.log(pos[i][j] + " " + x.invert(pos[i][j])); // Doesn't work because x doesn't have invert method
}
}
}
It's been a long time since I've coded. I've never looked into scripts for google spreadsheets before. I just want to make a simple effect to edit the spreadsheet. If I understand correctly, this is doable so long as you run it manually?
The syntax is throwing me off too much. My basic goal is to set each cell in a fixed column range to equal itself plus the value in the adjacent column, and then set that second value to 0.
My instinct would be to do something such as
CellRange[i][j] selected = C9:D13;
for(i=0,i<selectedrange.length,i++){
SpreadsheetApp.getActiveRange().setValue(selected[i][j]+selected[i][j+1];
SpreadsheetApp.getRange(selected[i][j+1]).setValue(0);
}
That's probably terribly wrong but I feel I ought to at least throw my best guess out before asking for help.
Say, the goal is to process the range C9:D13 by adding the value in D to the value in C, and then setting D to zero. The code would look like this:
function addColumns() {
var sheet = SpreadsheetApp.getActiveSheet(); // or getSheetByName
var range = sheet.getRange("C9:D13");
var values = range.getValues();
for (var i = 0; i < values.length; i++) {
values[i][0] = values[i][0] + values[i][1];
values[i][1] = 0;
}
range.setValues(values);
}
Here, values[i][0] means values the first column in the range we're working on (namely C) and values[i][1] refers to the second. The indexing of JavaScript arrays begins with 0, unlike the numbering of rows in spreadsheets.